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style(notebooks): apply Ruff formatter
1 parent 147fa71 commit 049bd03

5 files changed

Lines changed: 307 additions & 192 deletions

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‎01_QC_n_tax_id/01_Lab_journal.ipynb‎

Lines changed: 14 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -72,12 +72,12 @@
7272
"outputs": [],
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"source": [
7474
"# Directory with the source sequences\n",
75-
"raw_sequences_dir = 'samples/raw_sequences'\n",
75+
"raw_sequences_dir = \"samples/raw_sequences\"\n",
7676
"# Directory for merged sequences\n",
77-
"unified_sequences_dir = 'samples/unified_sequences'\n",
77+
"unified_sequences_dir = \"samples/unified_sequences\"\n",
7878
"\n",
7979
"# List of sample folders\n",
80-
"samples = ['D1', 'D2', 'D3', 'D4', 'D5', 'P1', 'P2', 'P3', 'P4', 'P5']\n",
80+
"samples = [\"D1\", \"D2\", \"D3\", \"D4\", \"D5\", \"P1\", \"P2\", \"P3\", \"P4\", \"P5\"]\n",
8181
"\n",
8282
"# Create a directory for merged sequences, if it does not exist\n",
8383
"if not os.path.exists(unified_sequences_dir):\n",
@@ -88,25 +88,25 @@
8888
" sample_dir = os.path.join(raw_sequences_dir, sample)\n",
8989
" # Folder path for merged files of the current sample\n",
9090
" sample_output_dir = os.path.join(unified_sequences_dir, sample)\n",
91-
" \n",
91+
"\n",
9292
" # Create a folder for merged files, if there is no such folder\n",
9393
" if not os.path.exists(sample_output_dir):\n",
9494
" os.makedirs(sample_output_dir)\n",
95-
" \n",
95+
"\n",
9696
" # File paths to be merged\n",
97-
" r1_files_pattern = os.path.join(sample_dir, '*_R1_*.fastq.gz')\n",
98-
" r2_files_pattern = os.path.join(sample_dir, '*_R2_*.fastq.gz')\n",
99-
" \n",
97+
" r1_files_pattern = os.path.join(sample_dir, \"*_R1_*.fastq.gz\")\n",
98+
" r2_files_pattern = os.path.join(sample_dir, \"*_R2_*.fastq.gz\")\n",
99+
"\n",
100100
" # Paths for saving merged files\n",
101-
" combined_r1_path = os.path.join(sample_output_dir, f'{sample}_combined_R1.fastq.gz')\n",
102-
" combined_r2_path = os.path.join(sample_output_dir, f'{sample}_combined_R2.fastq.gz')\n",
103-
" \n",
101+
" combined_r1_path = os.path.join(sample_output_dir, f\"{sample}_combined_R1.fastq.gz\")\n",
102+
" combined_r2_path = os.path.join(sample_output_dir, f\"{sample}_combined_R2.fastq.gz\")\n",
103+
"\n",
104104
" # Merging R1 files\n",
105-
" cat_r1_command = f'cat {r1_files_pattern} > {combined_r1_path}'\n",
105+
" cat_r1_command = f\"cat {r1_files_pattern} > {combined_r1_path}\"\n",
106106
" os.system(cat_r1_command)\n",
107-
" \n",
107+
"\n",
108108
" # Merging R2 files\n",
109-
" cat_r2_command = f'cat {r2_files_pattern} > {combined_r2_path}'\n",
109+
" cat_r2_command = f\"cat {r2_files_pattern} > {combined_r2_path}\"\n",
110110
" os.system(cat_r2_command)\n",
111111
"\n",
112112
"print(\"File merge completed.\")"

‎02_Diff_analysis/02_Lab_journal.ipynb‎

Lines changed: 43 additions & 29 deletions
Original file line numberDiff line numberDiff line change
@@ -88,7 +88,7 @@
8888
},
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{
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"cell_type": "code",
91-
"execution_count": 3,
91+
"execution_count": null,
9292
"metadata": {},
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"outputs": [
9494
{
@@ -331,7 +331,9 @@
331331
"df = pd.read_csv(\"data/counts/csv/counts_species.csv\")\n",
332332
"\n",
333333
"# Переименование колонки\n",
334-
"df.rename(columns={\"Blattambidensovirus incertum1\": \"Parus major densovirus\"}, inplace=True)\n",
334+
"df.rename(\n",
335+
" columns={\"Blattambidensovirus incertum1\": \"Parus major densovirus\"}, inplace=True\n",
336+
")\n",
335337
"\n",
336338
"# Сохранение обратно в CSV (если нужно)\n",
337339
"df.to_csv(\"data/counts/csv/counts_species_new.csv\", index=False)\n",
@@ -358,7 +360,7 @@
358360
},
359361
{
360362
"cell_type": "code",
361-
"execution_count": 2,
363+
"execution_count": null,
362364
"metadata": {},
363365
"outputs": [
364366
{
@@ -372,28 +374,28 @@
372374
"source": [
373375
"# Define the data\n",
374376
"data = [\n",
375-
" {'sample_id': 'D1', 'Group': 'Vespertilio murinus'},\n",
376-
" {'sample_id': 'D2', 'Group': 'Vespertilio murinus'},\n",
377-
" {'sample_id': 'D3', 'Group': 'Vespertilio murinus'},\n",
378-
" {'sample_id': 'D4', 'Group': 'Vespertilio murinus'},\n",
379-
" {'sample_id': 'D5', 'Group': 'Vespertilio murinus'},\n",
380-
" {'sample_id': 'P1', 'Group': 'Nyctalus noctula'},\n",
381-
" {'sample_id': 'P2', 'Group': 'Nyctalus noctula'},\n",
382-
" {'sample_id': 'P3', 'Group': 'Nyctalus noctula'},\n",
383-
" {'sample_id': 'P4', 'Group': 'Nyctalus noctula'},\n",
384-
" {'sample_id': 'P5', 'Group': 'Nyctalus noctula'}\n",
377+
" {\"sample_id\": \"D1\", \"Group\": \"Vespertilio murinus\"},\n",
378+
" {\"sample_id\": \"D2\", \"Group\": \"Vespertilio murinus\"},\n",
379+
" {\"sample_id\": \"D3\", \"Group\": \"Vespertilio murinus\"},\n",
380+
" {\"sample_id\": \"D4\", \"Group\": \"Vespertilio murinus\"},\n",
381+
" {\"sample_id\": \"D5\", \"Group\": \"Vespertilio murinus\"},\n",
382+
" {\"sample_id\": \"P1\", \"Group\": \"Nyctalus noctula\"},\n",
383+
" {\"sample_id\": \"P2\", \"Group\": \"Nyctalus noctula\"},\n",
384+
" {\"sample_id\": \"P3\", \"Group\": \"Nyctalus noctula\"},\n",
385+
" {\"sample_id\": \"P4\", \"Group\": \"Nyctalus noctula\"},\n",
386+
" {\"sample_id\": \"P5\", \"Group\": \"Nyctalus noctula\"},\n",
385387
"]\n",
386388
"\n",
387389
"# Define the CSV file name\n",
388-
"filename = 'metadata.csv'\n",
390+
"filename = \"metadata.csv\"\n",
389391
"\n",
390392
"# Write the data to the CSV file\n",
391-
"with open(filename, mode='w', newline='') as file:\n",
392-
" writer = csv.DictWriter(file, fieldnames=['sample_id', 'Group'])\n",
393+
"with open(filename, mode=\"w\", newline=\"\") as file:\n",
394+
" writer = csv.DictWriter(file, fieldnames=[\"sample_id\", \"Group\"])\n",
393395
" writer.writeheader()\n",
394396
" writer.writerows(data)\n",
395397
"\n",
396-
"print(f'{filename} has been created successfully.')"
398+
"print(f\"{filename} has been created successfully.\")"
397399
]
398400
},
399401
{
@@ -449,7 +451,7 @@
449451
},
450452
{
451453
"cell_type": "code",
452-
"execution_count": 53,
454+
"execution_count": null,
453455
"metadata": {},
454456
"outputs": [
455457
{
@@ -501,7 +503,9 @@
501503
}
502504
],
503505
"source": [
504-
"MaAsLin2_results_species = pd.read_csv('MaAsLin2_results/species/significant_results.tsv', sep='\\t')\n",
506+
"MaAsLin2_results_species = pd.read_csv(\n",
507+
" \"MaAsLin2_results/species/significant_results.tsv\", sep=\"\\t\"\n",
508+
")\n",
505509
"MaAsLin2_results_species"
506510
]
507511
},
@@ -526,7 +530,7 @@
526530
},
527531
{
528532
"cell_type": "code",
529-
"execution_count": 55,
533+
"execution_count": null,
530534
"metadata": {},
531535
"outputs": [
532536
{
@@ -578,7 +582,9 @@
578582
}
579583
],
580584
"source": [
581-
"MaAsLin2_results_species = pd.read_csv('MaAsLin2_results/genus/significant_results.tsv', sep='\\t')\n",
585+
"MaAsLin2_results_species = pd.read_csv(\n",
586+
" \"MaAsLin2_results/genus/significant_results.tsv\", sep=\"\\t\"\n",
587+
")\n",
582588
"MaAsLin2_results_species"
583589
]
584590
},
@@ -603,7 +609,7 @@
603609
},
604610
{
605611
"cell_type": "code",
606-
"execution_count": 57,
612+
"execution_count": null,
607613
"metadata": {},
608614
"outputs": [
609615
{
@@ -655,7 +661,9 @@
655661
}
656662
],
657663
"source": [
658-
"MaAsLin2_results_family = pd.read_csv('MaAsLin2_results/family/significant_results.tsv', sep='\\t')\n",
664+
"MaAsLin2_results_family = pd.read_csv(\n",
665+
" \"MaAsLin2_results/family/significant_results.tsv\", sep=\"\\t\"\n",
666+
")\n",
659667
"MaAsLin2_results_family"
660668
]
661669
},
@@ -680,7 +688,7 @@
680688
},
681689
{
682690
"cell_type": "code",
683-
"execution_count": 59,
691+
"execution_count": null,
684692
"metadata": {},
685693
"outputs": [
686694
{
@@ -732,7 +740,9 @@
732740
}
733741
],
734742
"source": [
735-
"MaAsLin2_results_order = pd.read_csv('MaAsLin2_results/order/significant_results.tsv', sep='\\t')\n",
743+
"MaAsLin2_results_order = pd.read_csv(\n",
744+
" \"MaAsLin2_results/order/significant_results.tsv\", sep=\"\\t\"\n",
745+
")\n",
736746
"MaAsLin2_results_order"
737747
]
738748
},
@@ -757,7 +767,7 @@
757767
},
758768
{
759769
"cell_type": "code",
760-
"execution_count": 61,
770+
"execution_count": null,
761771
"metadata": {},
762772
"outputs": [
763773
{
@@ -809,7 +819,9 @@
809819
}
810820
],
811821
"source": [
812-
"MaAsLin2_results_class = pd.read_csv('MaAsLin2_results/class/significant_results.tsv', sep='\\t')\n",
822+
"MaAsLin2_results_class = pd.read_csv(\n",
823+
" \"MaAsLin2_results/class/significant_results.tsv\", sep=\"\\t\"\n",
824+
")\n",
813825
"MaAsLin2_results_class"
814826
]
815827
},
@@ -834,7 +846,7 @@
834846
},
835847
{
836848
"cell_type": "code",
837-
"execution_count": 63,
849+
"execution_count": null,
838850
"metadata": {},
839851
"outputs": [
840852
{
@@ -886,7 +898,9 @@
886898
}
887899
],
888900
"source": [
889-
"MaAsLin2_results_phylum = pd.read_csv('MaAsLin2_results/phylum/significant_results.tsv', sep='\\t')\n",
901+
"MaAsLin2_results_phylum = pd.read_csv(\n",
902+
" \"MaAsLin2_results/phylum/significant_results.tsv\", sep=\"\\t\"\n",
903+
")\n",
890904
"MaAsLin2_results_phylum"
891905
]
892906
},

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